DBMS > Apache Pinot vs. ClickHouse vs. DuckDB

System Properties Comparison Apache Pinot vs. ClickHouse vs. DuckDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.35
Rank	#271	Overall
	#124	Relational DBMS

Score	18.56
Rank	#30	Overall
	#18	Relational DBMS

Score	6.32
Rank	#55	Overall
	#33	Relational DBMS

Website

pinot.apache.org

clickhouse.com

duckdb.org

Technical documentation

docs.pinot.apache.org

clickhouse.com/docs

duckdb.org/docs

Developer

Apache Software Foundation and contributors

Clickhouse Inc.

Initial release

2015

2016

2018

Current release

1.0.0, September 2023

v24.6.2.17-stable, July 2024

1.0.0, June 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

All OS with a Java JDK11 or higher

FreeBSD
Linux
macOS

server-less

Data scheme

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

JDBC

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

key based and custom

none

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Build a real-time analytics solution with Apache Pinot on AWS
6 August 2024, AWS Blog

Serving Millions of Apache Pinot™ Queries with Neutrino
11 December 2024, Uber

Apache Pinot Brings Real Time Analysis to Columnar Data
13 December 2024, The New Stack

StarTree eyes observability market with Apache Pinot-based real-time engine
27 September 2024, SiliconANGLE News

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

provided by Google News

A Beginner’s Guide to ClickHouse Database
13 September 2024, KDnuggets

ClickHouse Announces Strategic Collaboration Agreement with AWS to Advance Real-Time Data Analytics and Generative AI Innovation
10 December 2024, Business Wire

Azur Games migrates all game analytics data to ClickHouse Cloud on AWS
16 July 2024, AWS Blog

Real-time database startup ClickHouse acquires PeerDB to expand its Postgres support
30 July 2024, TechCrunch

Database startup ClickHouse Announces PeerDB Acquistion
31 July 2024, Tech Times

provided by Google News

A Guide to Data Analysis in Python with DuckDB
18 November 2024, KDnuggets

AWS Lambda + DuckDB (and Delta Lake)
29 December 2024, substack.com

MotherDuck Announces Beta Release of pg_duckdb; Brings DuckDB's Analytics Power to PostgreSQL Users
24 October 2024, PR Newswire

Handling Billions of Records in Minutes with SQL ⏱️
23 December 2024, Towards Data Science

DuckDB And Hydra Partner To Get DuckDB Into PostgreSQL
11 November 2024, iProgrammer

provided by Google News

Share this page